Pandas Profiling Report

Dataset statistics

Number of variables	43
Number of observations	1339
Missing cells	3990
Missing cells (%)	6.9%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	2.4 MiB
Average record size in memory	1.8 KiB

Variable types

Categorical	24
Numeric	19

Alerts

`Owner` has a high cardinality: 315 distinct values	High cardinality
`Farm.Name` has a high cardinality: 571 distinct values	High cardinality
`Lot.Number` has a high cardinality: 227 distinct values	High cardinality
`Mill` has a high cardinality: 459 distinct values	High cardinality
`ICO.Number` has a high cardinality: 847 distinct values	High cardinality
`Company` has a high cardinality: 281 distinct values	High cardinality
`Altitude` has a high cardinality: 396 distinct values	High cardinality
`Region` has a high cardinality: 356 distinct values	High cardinality
`Producer` has a high cardinality: 692 distinct values	High cardinality
`Bag.Weight` has a high cardinality: 56 distinct values	High cardinality
`Grading.Date` has a high cardinality: 567 distinct values	High cardinality
`Owner.1` has a high cardinality: 319 distinct values	High cardinality
`Expiration` has a high cardinality: 566 distinct values	High cardinality
`Aroma` is highly correlated with `Flavor` and 6 other fields	High correlation
`Flavor` is highly correlated with `Aroma` and 6 other fields	High correlation
`Aftertaste` is highly correlated with `Aroma` and 6 other fields	High correlation
`Acidity` is highly correlated with `Aroma` and 6 other fields	High correlation
`Body` is highly correlated with `Aroma` and 6 other fields	High correlation
`Balance` is highly correlated with `Aroma` and 6 other fields	High correlation
`Uniformity` is highly correlated with `Clean.Cup`	High correlation
`Clean.Cup` is highly correlated with `Uniformity`	High correlation
`Cupper.Points` is highly correlated with `Aroma` and 6 other fields	High correlation
`Total.Cup.Points` is highly correlated with `Aroma` and 6 other fields	High correlation
`altitude_low_meters` is highly correlated with `altitude_high_meters` and 1 other fields	High correlation
`altitude_high_meters` is highly correlated with `altitude_low_meters` and 1 other fields	High correlation
`altitude_mean_meters` is highly correlated with `altitude_low_meters` and 1 other fields	High correlation
`Aroma` is highly correlated with `Flavor` and 6 other fields	High correlation
`Flavor` is highly correlated with `Aroma` and 6 other fields	High correlation
`Aftertaste` is highly correlated with `Aroma` and 6 other fields	High correlation
`Acidity` is highly correlated with `Aroma` and 6 other fields	High correlation
`Body` is highly correlated with `Aroma` and 6 other fields	High correlation
`Balance` is highly correlated with `Aroma` and 6 other fields	High correlation
`Uniformity` is highly correlated with `Clean.Cup` and 1 other fields	High correlation
`Clean.Cup` is highly correlated with `Uniformity` and 1 other fields	High correlation
`Sweetness` is highly correlated with `Total.Cup.Points`	High correlation
`Cupper.Points` is highly correlated with `Aroma` and 6 other fields	High correlation
`Total.Cup.Points` is highly correlated with `Aroma` and 9 other fields	High correlation
`altitude_low_meters` is highly correlated with `altitude_high_meters` and 1 other fields	High correlation
`altitude_high_meters` is highly correlated with `altitude_low_meters` and 1 other fields	High correlation
`altitude_mean_meters` is highly correlated with `altitude_low_meters` and 1 other fields	High correlation
`Aroma` is highly correlated with `Flavor` and 3 other fields	High correlation
`Flavor` is highly correlated with `Aroma` and 6 other fields	High correlation
`Aftertaste` is highly correlated with `Aroma` and 6 other fields	High correlation
`Acidity` is highly correlated with `Flavor` and 4 other fields	High correlation
`Body` is highly correlated with `Flavor` and 4 other fields	High correlation
`Balance` is highly correlated with `Flavor` and 5 other fields	High correlation
`Uniformity` is highly correlated with `Clean.Cup`	High correlation
`Clean.Cup` is highly correlated with `Uniformity`	High correlation
`Cupper.Points` is highly correlated with `Aroma` and 6 other fields	High correlation
`Total.Cup.Points` is highly correlated with `Aroma` and 6 other fields	High correlation
`altitude_low_meters` is highly correlated with `altitude_high_meters` and 1 other fields	High correlation
`altitude_high_meters` is highly correlated with `altitude_low_meters` and 1 other fields	High correlation
`altitude_mean_meters` is highly correlated with `altitude_low_meters` and 1 other fields	High correlation
`Bag.Weight` is highly correlated with `unit_of_measurement`	High correlation
`Variety` is highly correlated with `unit_of_measurement`	High correlation
`Country.of.Origin` is highly correlated with `Certification.Address` and 5 other fields	High correlation
`Certification.Address` is highly correlated with `Country.of.Origin` and 5 other fields	High correlation
`Species` is highly correlated with `Country.of.Origin` and 2 other fields	High correlation
`Certification.Body` is highly correlated with `Country.of.Origin` and 4 other fields	High correlation
`Certification.Contact` is highly correlated with `Country.of.Origin` and 5 other fields	High correlation
`In.Country.Partner` is highly correlated with `Country.of.Origin` and 4 other fields	High correlation
`unit_of_measurement` is highly correlated with `Bag.Weight` and 6 other fields	High correlation
`Species` is highly correlated with `Country.of.Origin` and 3 other fields	High correlation
`Country.of.Origin` is highly correlated with `Species` and 16 other fields	High correlation
`Number.of.Bags` is highly correlated with `Country.of.Origin` and 6 other fields	High correlation
`Bag.Weight` is highly correlated with `Country.of.Origin` and 11 other fields	High correlation
`In.Country.Partner` is highly correlated with `Country.of.Origin` and 11 other fields	High correlation
`Harvest.Year` is highly correlated with `Country.of.Origin` and 8 other fields	High correlation
`Variety` is highly correlated with `Country.of.Origin` and 9 other fields	High correlation
`Processing.Method` is highly correlated with `Country.of.Origin` and 6 other fields	High correlation
`Aroma` is highly correlated with `Flavor` and 9 other fields	High correlation
`Flavor` is highly correlated with `Aroma` and 9 other fields	High correlation
`Aftertaste` is highly correlated with `Country.of.Origin` and 10 other fields	High correlation
`Acidity` is highly correlated with `Aroma` and 9 other fields	High correlation
`Body` is highly correlated with `Country.of.Origin` and 10 other fields	High correlation
`Balance` is highly correlated with `Country.of.Origin` and 10 other fields	High correlation
`Uniformity` is highly correlated with `Aroma` and 9 other fields	High correlation
`Clean.Cup` is highly correlated with `Aroma` and 9 other fields	High correlation
`Sweetness` is highly correlated with `Species` and 13 other fields	High correlation
`Cupper.Points` is highly correlated with `Bag.Weight` and 11 other fields	High correlation
`Total.Cup.Points` is highly correlated with `Aroma` and 9 other fields	High correlation
`Moisture` is highly correlated with `Country.of.Origin` and 6 other fields	High correlation
`Category.One.Defects` is highly correlated with `Certification.Address` and 1 other fields	High correlation
`Quakers` is highly correlated with `altitude_low_meters` and 2 other fields	High correlation
`Color` is highly correlated with `Country.of.Origin` and 4 other fields	High correlation
`Category.Two.Defects` is highly correlated with `Certification.Address` and 1 other fields	High correlation
`Certification.Body` is highly correlated with `Country.of.Origin` and 11 other fields	High correlation
`Certification.Address` is highly correlated with `Species` and 15 other fields	High correlation
`Certification.Contact` is highly correlated with `Species` and 15 other fields	High correlation
`unit_of_measurement` is highly correlated with `Country.of.Origin` and 6 other fields	High correlation
`altitude_low_meters` is highly correlated with `Quakers` and 2 other fields	High correlation
`altitude_high_meters` is highly correlated with `Quakers` and 2 other fields	High correlation
`altitude_mean_meters` is highly correlated with `Quakers` and 2 other fields	High correlation
`Farm.Name` has 359 (26.8%) missing values	Missing
`Lot.Number` has 1063 (79.4%) missing values	Missing
`Mill` has 318 (23.7%) missing values	Missing
`ICO.Number` has 157 (11.7%) missing values	Missing
`Company` has 209 (15.6%) missing values	Missing
`Altitude` has 226 (16.9%) missing values	Missing
`Region` has 59 (4.4%) missing values	Missing
`Producer` has 232 (17.3%) missing values	Missing
`Harvest.Year` has 47 (3.5%) missing values	Missing
`Variety` has 226 (16.9%) missing values	Missing
`Processing.Method` has 170 (12.7%) missing values	Missing
`Color` has 218 (16.3%) missing values	Missing
`altitude_low_meters` has 230 (17.2%) missing values	Missing
`altitude_high_meters` has 230 (17.2%) missing values	Missing
`altitude_mean_meters` has 230 (17.2%) missing values	Missing
`altitude_low_meters` is highly skewed (γ1 = 20.3231837)	Skewed
`altitude_high_meters` is highly skewed (γ1 = 20.31093398)	Skewed
`altitude_mean_meters` is highly skewed (γ1 = 20.32052739)	Skewed
`Moisture` has 264 (19.7%) zeros	Zeros
`Category.One.Defects` has 1137 (84.9%) zeros	Zeros
`Quakers` has 1244 (92.9%) zeros	Zeros
`Category.Two.Defects` has 373 (27.9%) zeros	Zeros

Reproduction

Analysis started	2022-03-15 14:45:51.722969
Analysis finished	2022-03-15 14:47:10.562455
Duration	1 minute and 18.84 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

Species
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	94.1 KiB

Arabica	1311
Robusta	28

Length

Max length	7
Median length	7
Mean length	7
Min length	7

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Arabica
2nd row	Arabica
3rd row	Arabica
4th row	Arabica
5th row	Arabica

Common Values

Value	Count	Frequency (%)
Arabica	1311	97.9%
Robusta	28	2.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
arabica	1311	97.9%
robusta	28	2.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Owner
Categorical

HIGH CARDINALITY

Distinct	315
Distinct (%)	23.6%
Missing	7
Missing (%)	0.5%
Memory size	117.1 KiB

juan luis alvarado romero	155
racafe & cia s.c.a	60
exportadora de cafe condor s.a	54
kona pacific farmers cooperative	52
ipanema coffees	50
Other values (310)	961

Length

Max length	50
Median length	22
Mean length	21.21321321
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	172 ?
Unique (%)	12.9%

Sample

1st row	metad plc
2nd row	metad plc
3rd row	grounds for health admin
4th row	yidnekachew dabessa
5th row	metad plc

Common Values

Value	Count	Frequency (%)
juan luis alvarado romero	155	11.6%
racafe & cia s.c.a	60	4.5%
exportadora de cafe condor s.a	54	4.0%
kona pacific farmers cooperative	52	3.9%
ipanema coffees	50	3.7%
cqi taiwan icp cqi台灣合作夥伴	47	3.5%
lin, che-hao krude 林哲豪	30	2.2%
nucoffee	29	2.2%
carcafe ltda ci	27	2.0%
the coffee source inc.	23	1.7%
Other values (305)	805	60.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
luis	169	3.9%
juan	160	3.7%
alvarado	155	3.6%
romero	155	3.6%
de	114	2.6%
s.a	101	2.3%
coffee	87	2.0%
cafe	74	1.7%
exportadora	70	1.6%
coffees	67	1.6%
Other values (655)	3170	73.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Country.of.Origin
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	36
Distinct (%)	2.7%
Missing	1
Missing (%)	0.1%
Memory size	96.5 KiB

Mexico	236
Colombia	183
Guatemala	181
Brazil	132
Taiwan	75
Other values (31)	531

Length

Max length	28
Median length	8
Mean length	8.835575486
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	6 ?
Unique (%)	0.4%

Sample

1st row	Ethiopia
2nd row	Ethiopia
3rd row	Guatemala
4th row	Ethiopia
5th row	Ethiopia

Common Values

Value	Count	Frequency (%)
Mexico	236	17.6%
Colombia	183	13.7%
Guatemala	181	13.5%
Brazil	132	9.9%
Taiwan	75	5.6%
United States (Hawaii)	73	5.5%
Honduras	53	4.0%
Costa Rica	51	3.8%
Ethiopia	44	3.3%
Tanzania, United Republic Of	40	3.0%
Other values (26)	270	20.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
mexico	236	13.9%
colombia	183	10.8%
guatemala	181	10.6%
brazil	132	7.8%
united	127	7.5%
states	87	5.1%
taiwan	75	4.4%
hawaii	73	4.3%
honduras	53	3.1%
costa	51	3.0%
Other values (35)	503	29.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Farm.Name
Categorical

HIGH CARDINALITY
MISSING

Distinct	571
Distinct (%)	58.3%
Missing	359
Missing (%)	26.8%
Memory size	95.5 KiB

various	47
rio verde	23
several	20
finca medina	15
doi tung development project	13
Other values (566)	862

Length

Max length	73
Median length	13
Mean length	15.3622449
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	438 ?
Unique (%)	44.7%

Sample

1st row	metad plc
2nd row	metad plc
3rd row	san marcos barrancas "san cristobal cuch
4th row	yidnekachew dabessa coffee plantation
5th row	metad plc

Common Values

Value	Count	Frequency (%)
various	47	3.5%
rio verde	23	1.7%
several	20	1.5%
finca medina	15	1.1%
doi tung development project	13	1.0%
fazenda capoeirnha	13	1.0%
conquista / morito	11	0.8%
los hicaques	11	0.8%
capoeirinha	10	0.7%
el papaturro	9	0.7%
Other values (561)	808	60.3%
(Missing)	359	26.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
el	96	4.0%
la	87	3.6%
finca	79	3.3%
coffee	74	3.1%
various	47	2.0%
estate	44	1.8%
santa	40	1.7%
	40	1.7%
fazenda	39	1.6%
los	36	1.5%
Other values (856)	1814	75.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Lot.Number
Categorical

HIGH CARDINALITY
MISSING

Distinct	227
Distinct (%)	82.2%
Missing	1063
Missing (%)	79.4%
Memory size	62.4 KiB

1	18
020/17	6
019/17	5
103	3
2016 Tainan Coffee Cupping Event Micro Lot 臺南市咖啡評鑑批次	3
Other values (222)	241

Length

Max length	71
Median length	9
Mean length	9.891304348
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	205 ?
Unique (%)	74.3%

Sample

1st row	YNC-06114
2nd row	102
3rd row	Tsoustructive 2015 Sumatra Typica
4th row	11/23/0252
5th row	Baby Geisha Washed

Common Values

Value	Count	Frequency (%)
1	18	1.3%
020/17	6	0.4%
019/17	5	0.4%
103	3	0.2%
2016 Tainan Coffee Cupping Event Micro Lot 臺南市咖啡評鑑批次	3	0.2%
2	3	0.2%
102	3	0.2%
43102245 - P4615	2	0.1%
63	2	0.1%
47	2	0.1%
Other values (217)	229	17.1%
(Missing)	1063	79.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
1	19	4.9%
	11	2.8%
coffee	10	2.6%
020/17	6	1.5%
lot	6	1.5%
tainan	6	1.5%
2017	5	1.3%
event	5	1.3%
019/17	5	1.3%
evaluation	5	1.3%
Other values (257)	313	80.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Mill
Categorical

HIGH CARDINALITY
MISSING

Distinct	459
Distinct (%)	45.0%
Missing	318
Missing (%)	23.7%
Memory size	100.4 KiB

beneficio ixchel	90
dry mill	39
trilladora boananza	38
ipanema coffees	16
neiva	15
Other values (454)	823

Length

Max length	77
Median length	17
Mean length	19.06170421
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	309 ?
Unique (%)	30.3%

Sample

1st row	metad plc
2nd row	metad plc
3rd row	wolensu
4th row	metad plc
5th row	hvc

Common Values

Value	Count	Frequency (%)
beneficio ixchel	90	6.7%
dry mill	39	2.9%
trilladora boananza	38	2.8%
ipanema coffees	16	1.2%
neiva	15	1.1%
bachue	14	1.0%
cigrah s.a de c.v.	12	0.9%
trilladora bonanza - armenia quindioa	12	0.9%
cadexsa	12	0.9%
beneficio siembras vision (154)	12	0.9%
Other values (449)	761	56.8%
(Missing)	318	23.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
beneficio	181	6.2%
de	105	3.6%
ixchel	93	3.2%
coffee	91	3.1%
trilladora	68	2.3%
mill	48	1.6%
dry	46	1.6%
la	39	1.3%
boananza	38	1.3%
el	38	1.3%
Other values (796)	2186	74.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

ICO.Number
Categorical

HIGH CARDINALITY
MISSING

Distinct	847
Distinct (%)	71.7%
Missing	157
Missing (%)	11.7%
Memory size	91.9 KiB

0	77
Taiwan	31
2222	11
-	9
002/1660/0105	7
Other values (842)	1047

Length

Max length	40
Median length	9
Mean length	8.972081218
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	719 ?
Unique (%)	60.8%

Sample

1st row	2014/2015
2nd row	2014/2015
3rd row	2014/2015
4th row	010/0338
5th row	010/0338

Common Values

Value	Count	Frequency (%)
0	77	5.8%
Taiwan	31	2.3%
2222	11	0.8%
-	9	0.7%
002/1660/0105	7	0.5%
Taiwan台灣	7	0.5%
002/4177/0150	7	0.5%
002/1660/0080	6	0.4%
1	6	0.4%
unknown	6	0.4%
Other values (837)	1015	75.8%
(Missing)	157	11.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
0	77	5.9%
taiwan	31	2.4%
	21	1.6%
hdoa	16	1.2%
2222	11	0.8%
none	10	0.8%
kona	9	0.7%
1	8	0.6%
002/4177/0150	7	0.5%
taiwan台灣	7	0.5%
Other values (879)	1099	84.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Company
Categorical

HIGH CARDINALITY
MISSING

Distinct	281
Distinct (%)	24.9%
Missing	209
Missing (%)	15.6%
Memory size	106.1 KiB

unex guatemala, s.a.	86
ipanema coffees	50
kona pacific farmers cooperative	40
racafe & cia s.c.a	40
exportadora de cafe condor s.a	40
Other values (276)	874

Length

Max length	78
Median length	20
Mean length	21.09469027
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	143 ?
Unique (%)	12.7%

Sample

1st row	metad agricultural developmet plc
2nd row	metad agricultural developmet plc
3rd row	yidnekachew debessa coffee plantation
4th row	metad agricultural developmet plc
5th row	richmond investment-coffee department

Common Values

Value	Count	Frequency (%)
unex guatemala, s.a.	86	6.4%
ipanema coffees	50	3.7%
kona pacific farmers cooperative	40	3.0%
racafe & cia s.c.a	40	3.0%
exportadora de cafe condor s.a	40	3.0%
blossom valley宸嶧國際	25	1.9%
carcafe ltda	25	1.9%
nucoffee	24	1.8%
taiwan coffee laboratory	20	1.5%
ecomtrading	19	1.4%
Other values (271)	761	56.8%
(Missing)	209	15.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
s.a	246	6.7%
de	215	5.9%
coffee	185	5.0%
guatemala	104	2.8%
ltd	87	2.4%
unex	86	2.3%
exportadora	70	1.9%
cafe	70	1.9%
coffees	69	1.9%
	64	1.7%
Other values (519)	2479	67.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Altitude
Categorical

HIGH CARDINALITY
MISSING

Distinct	396
Distinct (%)	35.6%
Missing	226
Missing (%)	16.9%
Memory size	86.6 KiB

1100	43
1200	42
1300	32
1400	32
4300	31
Other values (391)	933

Length

Max length	41
Median length	4
Mean length	6.355795148
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	251 ?
Unique (%)	22.6%

Sample

1st row	1950-2200
2nd row	1950-2200
3rd row	1600 - 1800 m
4th row	1800-2200
5th row	1950-2200

Common Values

Value	Count	Frequency (%)
1100	43	3.2%
1200	42	3.1%
1300	32	2.4%
1400	32	2.4%
4300	31	2.3%
1500	30	2.2%
1250	30	2.2%
1700	28	2.1%
1550	24	1.8%
1600	23	1.7%
Other values (386)	798	59.6%
(Missing)	226	16.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
msnm	105	6.6%
m	60	3.7%
1200	59	3.7%
1600	56	3.5%
1400	52	3.2%
1100	47	2.9%
1300	44	2.7%
1500	42	2.6%
1800	40	2.5%
a	36	2.2%
Other values (329)	1061	66.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Region
Categorical

HIGH CARDINALITY
MISSING

Distinct	356
Distinct (%)	27.8%
Missing	59
Missing (%)	4.4%
Memory size	99.9 KiB

huila	112
oriente	80
south of minas	68
kona	66
veracruz	35
Other values (351)	919

Length

Max length	76
Median length	8
Mean length	10.92265625
Min length	2

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	200 ?
Unique (%)	15.6%

Sample

1st row	guji-hambela
2nd row	guji-hambela
3rd row	oromia
4th row	guji-hambela
5th row	oromia

Common Values

Value	Count	Frequency (%)
huila	112	8.4%
oriente	80	6.0%
south of minas	68	5.1%
kona	66	4.9%
veracruz	35	2.6%
tarrazu	19	1.4%
comayagua	17	1.3%
san marcos	16	1.2%
huehuetenango	16	1.2%
marcala	15	1.1%
Other values (346)	836	62.4%
(Missing)	59	4.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
huila	114	5.3%
oriente	89	4.1%
minas	88	4.1%
south	73	3.4%
of	73	3.4%
kona	66	3.1%
de	41	1.9%
san	40	1.9%
veracruz	36	1.7%
chiapas	35	1.6%
Other values (488)	1495	69.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Producer
Categorical

HIGH CARDINALITY
MISSING

Distinct	692
Distinct (%)	62.5%
Missing	232
Missing (%)	17.3%
Memory size	106.5 KiB

La Plata	30
Ipanema Agrícola SA	22
Doi Tung Development Project	17
VARIOS	12
Ipanema Agricola	12
Other values (687)	1014

Length

Max length	100
Median length	19
Mean length	20.55826558
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	538 ?
Unique (%)	48.6%

Sample

1st row	METAD PLC
2nd row	METAD PLC
3rd row	Yidnekachew Dabessa Coffee Plantation
4th row	METAD PLC
5th row	HVC

Common Values

Value	Count	Frequency (%)
La Plata	30	2.2%
Ipanema Agrícola SA	22	1.6%
Doi Tung Development Project	17	1.3%
VARIOS	12	0.9%
Ipanema Agricola	12	0.9%
Ipanema Agricola S.A	11	0.8%
ROBERTO MONTERROSO	10	0.7%
Reinerio Zepeda	9	0.7%
LA PLATA	9	0.7%
AMILCAR LAPOLA	9	0.7%
Other values (682)	966	72.1%
(Missing)	232	17.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
de	86	2.5%
coffee	69	2.0%
	65	1.9%
la	60	1.7%
s.a	52	1.5%
ipanema	50	1.4%
plata	41	1.2%
agricola	37	1.1%
ltd	36	1.0%
sa	30	0.9%
Other values (1260)	2972	85.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Number.of.Bags
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	131
Distinct (%)	9.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	154.1829724

Minimum	0
Maximum	1062
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	14
median	175
Q3	275
95-th percentile	320
Maximum	1062
Range	1062
Interquartile range (IQR)	261

Descriptive statistics

Standard deviation	129.9871621
Coefficient of variation (CV)	0.8430708016
Kurtosis	0.221701387
Mean	154.1829724
Median Absolute Deviation (MAD)	125
Skewness	0.3139022021
Sum	206451
Variance	16896.66231
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
250	242	18.1%
275	176	13.1%
10	108	8.1%
1	95	7.1%
320	79	5.9%
300	74	5.5%
50	42	3.1%
100	40	3.0%
20	36	2.7%
2	29	2.2%
Other values (121)	418	31.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
1	95	7.1%
2	29	2.2%
3	18	1.3%
4	6	0.4%
5	14	1.0%
6	10	0.7%
7	8	0.6%
8	10	0.7%
9	1	0.1%

Value	Count	Frequency (%)
1062	1	0.1%
600	1	0.1%
550	2	0.1%
500	2	0.1%
450	2	0.1%
440	3	0.2%
400	1	0.1%
380	1	0.1%
377	1	0.1%
360	4	0.3%

Bag.Weight
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct	56
Distinct (%)	4.2%
Missing	0
Missing (%)	0.0%
Memory size	91.1 KiB

1 kg	331
60 kg	256
69 kg	200
70 kg	156
2 kg	122
Other values (51)	274

Length

Max length	8
Median length	5
Mean length	4.700522778
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	23 ?
Unique (%)	1.7%

Sample

1st row	60 kg
2nd row	60 kg
3rd row	1
4th row	60 kg
5th row	60 kg

Common Values

Value	Count	Frequency (%)
1 kg	331	24.7%
60 kg	256	19.1%
69 kg	200	14.9%
70 kg	156	11.7%
2 kg	122	9.1%
100 lbs	59	4.4%
30 kg	29	2.2%
5 lbs	23	1.7%
6	19	1.4%
20 kg	14	1.0%
Other values (46)	130	9.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
kg	1196	45.1%
1	347	13.1%
60	256	9.7%
69	200	7.5%
70	156	5.9%
2	129	4.9%
lbs	114	4.3%
100	60	2.3%
5	30	1.1%
30	29	1.1%
Other values (36)	134	5.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

In.Country.Partner
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	27
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	124.9 KiB

Specialty Coffee Association	313
AMECAFE	205
Almacafé	178
Asociacion Nacional Del Café	155
Brazil Specialty Coffee Association	67
Other values (22)	421

Length

Max length	85
Median length	28
Mean length	23.08812547
Min length	7

Characters and Unicode

Total characters	1
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	0.2%

Sample

1st row	METAD Agricultural Development plc
2nd row	METAD Agricultural Development plc
3rd row	Specialty Coffee Association
4th row	METAD Agricultural Development plc
5th row	METAD Agricultural Development plc

Common Values

Value	Count	Frequency (%)
Specialty Coffee Association	313	23.4%
AMECAFE	205	15.3%
Almacafé	178	13.3%
Asociacion Nacional Del Café	155	11.6%
Brazil Specialty Coffee Association	67	5.0%
Instituto Hondureño del Café	60	4.5%
Blossom Valley International	58	4.3%
Africa Fine Coffee Association	49	3.7%
Specialty Coffee Association of Costa Rica	42	3.1%
NUCOFFEE	36	2.7%
Other values (17)	176	13.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
coffee	590	15.3%
association	503	13.1%
specialty	449	11.7%
café	225	5.8%
del	224	5.8%
amecafe	205	5.3%
almacafé	178	4.6%
asociacion	155	4.0%
nacional	155	4.0%
of	68	1.8%
Other values (52)	1095	28.5%

Most occurring characters

Value	Count	Frequency (%)
	1	100.0%

Most occurring categories

Value	Count	Frequency (%)
Control	1	100.0%

Most frequent character per category

Control

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
	1	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	1	100.0%

Harvest.Year
Categorical

HIGH CORRELATION
MISSING

Distinct	46
Distinct (%)	3.6%
Missing	47
Missing (%)	3.5%
Memory size	89.8 KiB

2012	354
2014	233
2013	181
2015	129
2016	124
Other values (41)	271

Length

Max length	24
Median length	4
Mean length	4.722136223
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	22 ?
Unique (%)	1.7%

Sample

1st row	2014
2nd row	2014
3rd row	2014
4th row	2014
5th row	2013

Common Values

Value	Count	Frequency (%)
2012	354	26.4%
2014	233	17.4%
2013	181	13.5%
2015	129	9.6%
2016	124	9.3%
2017	70	5.2%
2013/2014	29	2.2%
2015/2016	28	2.1%
2011	26	1.9%
2017 / 2018	19	1.4%
Other values (36)	99	7.4%
(Missing)	47	3.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2012	354	25.6%
2014	233	16.9%
2013	181	13.1%
2016	130	9.4%
2015	129	9.3%
2017	95	6.9%
	31	2.2%
2011	30	2.2%
2013/2014	29	2.1%
2015/2016	28	2.0%
Other values (40)	142	10.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Grading.Date
Categorical

HIGH CARDINALITY

Distinct	567
Distinct (%)	42.3%
Missing	0
Missing (%)	0.0%
Memory size	106.7 KiB

July 11th, 2012	25
December 26th, 2013	24
June 6th, 2012	19
August 30th, 2012	18
July 26th, 2012	15
Other values (562)	1238

Length

Max length	20
Median length	16
Mean length	16.59148618
Min length	13

Characters and Unicode

Total characters	2
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	283 ?
Unique (%)	21.1%

Sample

1st row	April 4th, 2015
2nd row	April 4th, 2015
3rd row	May 31st, 2010
4th row	March 26th, 2015
5th row	April 4th, 2015

Common Values

Value	Count	Frequency (%)
July 11th, 2012	25	1.9%
December 26th, 2013	24	1.8%
June 6th, 2012	19	1.4%
August 30th, 2012	18	1.3%
July 26th, 2012	15	1.1%
October 8th, 2015	13	1.0%
March 29th, 2013	13	1.0%
September 27th, 2012	13	1.0%
June 17th, 2010	12	0.9%
October 20th, 2017	11	0.8%
Other values (557)	1176	87.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2012	316	7.9%
2014	262	6.5%
2015	197	4.9%
june	162	4.0%
2013	155	3.9%
2017	143	3.6%
july	130	3.2%
april	129	3.2%
may	128	3.2%
2016	127	3.2%
Other values (42)	2268	56.5%

Most occurring characters

Value	Count	Frequency (%)
	2	100.0%

Most occurring categories

Value	Count	Frequency (%)
Control	2	100.0%

Most frequent character per category

Control

Value	Count	Frequency (%)
	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	2	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
	2	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	2	100.0%

Owner.1
Categorical

HIGH CARDINALITY

Distinct	319
Distinct (%)	23.9%
Missing	7
Missing (%)	0.5%
Memory size	117.1 KiB

Juan Luis Alvarado Romero	155
Racafe & Cia S.C.A	60
Exportadora de Cafe Condor S.A	54
Kona Pacific Farmers Cooperative	52
Ipanema Coffees	50
Other values (314)	961

Length

Max length	50
Median length	22
Mean length	21.21246246
Min length	3

Characters and Unicode

Total characters	2
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	176 ?
Unique (%)	13.2%

Sample

1st row	metad plc
2nd row	metad plc
3rd row	Grounds for Health Admin
4th row	Yidnekachew Dabessa
5th row	metad plc

Common Values

Value	Count	Frequency (%)
Juan Luis Alvarado Romero	155	11.6%
Racafe & Cia S.C.A	60	4.5%
Exportadora de Cafe Condor S.A	54	4.0%
Kona Pacific Farmers Cooperative	52	3.9%
Ipanema Coffees	50	3.7%
CQI Taiwan ICP CQI台灣合作夥伴	46	3.4%
Lin, Che-Hao Krude 林哲豪	29	2.2%
NUCOFFEE	29	2.2%
CARCAFE LTDA CI	27	2.0%
The Coffee Source Inc.	23	1.7%
Other values (309)	807	60.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
luis	169	3.9%
juan	160	3.7%
alvarado	155	3.6%
romero	155	3.6%
de	114	2.6%
s.a	100	2.3%
coffee	87	2.0%
cafe	74	1.7%
exportadora	70	1.6%
coffees	67	1.6%
Other values (656)	3168	73.4%

Most occurring characters

Value	Count	Frequency (%)
	2	100.0%

Most occurring categories

Value	Count	Frequency (%)
Control	2	100.0%

Most frequent character per category

Control

Value	Count	Frequency (%)
	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	2	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
	2	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	2	100.0%

Variety
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	29
Distinct (%)	2.6%
Missing	226
Missing (%)	16.9%
Memory size	87.1 KiB

Caturra	256
Bourbon	226
Typica	211
Other	110
Catuai	74
Other values (24)	236

Length

Max length	21
Median length	7
Mean length	7.017070979
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	6 ?
Unique (%)	0.5%

Sample

1st row	Other
2nd row	Bourbon
3rd row	Other
4th row	Other
5th row	Other

Common Values

Value	Count	Frequency (%)
Caturra	256	19.1%
Bourbon	226	16.9%
Typica	211	15.8%
Other	110	8.2%
Catuai	74	5.5%
Hawaiian Kona	44	3.3%
Yellow Bourbon	35	2.6%
Mundo Novo	33	2.5%
Catimor	20	1.5%
SL14	17	1.3%
Other values (19)	87	6.5%
(Missing)	226	16.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
bourbon	261	21.1%
caturra	256	20.7%
typica	211	17.1%
other	110	8.9%
catuai	74	6.0%
hawaiian	44	3.6%
kona	44	3.6%
yellow	35	2.8%
mundo	33	2.7%
novo	33	2.7%
Other values (25)	134	10.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Processing.Method
Categorical

HIGH CORRELATION
MISSING

Distinct	5
Distinct (%)	0.4%
Missing	170
Missing (%)	12.7%
Memory size	95.5 KiB

Washed / Wet	815
Natural / Dry	258
Semi-washed / Semi-pulped	56
Other	26
Pulped natural / honey	14

Length

Max length	25
Median length	12
Mean length	12.8075278
Min length	5

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Washed / Wet
2nd row	Washed / Wet
3rd row	Natural / Dry
4th row	Washed / Wet
5th row	Natural / Dry

Common Values

Value	Count	Frequency (%)
Washed / Wet	815	60.9%
Natural / Dry	258	19.3%
Semi-washed / Semi-pulped	56	4.2%
Other	26	1.9%
Pulped natural / honey	14	1.0%
(Missing)	170	12.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	1143	32.9%
washed	815	23.5%
wet	815	23.5%
natural	272	7.8%
dry	258	7.4%
semi-washed	56	1.6%
semi-pulped	56	1.6%
other	26	0.7%
pulped	14	0.4%
honey	14	0.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Aroma
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	33
Distinct (%)	2.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.566706497

Minimum	0
Maximum	8.75
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	7.08
Q1	7.42
median	7.58
Q3	7.75
95-th percentile	8.08
Maximum	8.75
Range	8.75
Interquartile range (IQR)	0.33

Descriptive statistics

Standard deviation	0.377559997
Coefficient of variation (CV)	0.0498975343
Kurtosis	121.4173128
Mean	7.566706497
Median Absolute Deviation (MAD)	0.17
Skewness	-6.245392604
Sum	10131.82
Variance	0.1425515513
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=33)

Value	Count	Frequency (%)
7.67	179	13.4%
7.5	165	12.3%
7.58	152	11.4%
7.75	125	9.3%
7.42	122	9.1%
7.83	103	7.7%
7.33	98	7.3%
7.25	78	5.8%
7.92	59	4.4%
8	48	3.6%
Other values (23)	210	15.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
5.08	1	0.1%
6.17	1	0.1%
6.33	1	0.1%
6.42	1	0.1%
6.5	2	0.1%
6.67	3	0.2%
6.75	7	0.5%
6.83	9	0.7%
6.92	14	1.0%

Value	Count	Frequency (%)
8.75	1	0.1%
8.67	2	0.1%
8.58	1	0.1%
8.5	3	0.2%
8.42	9	0.7%
8.33	7	0.5%
8.25	9	0.7%
8.17	20	1.5%
8.08	20	1.5%
8	48	3.6%

Flavor
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	35
Distinct (%)	2.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.520425691

Minimum	0
Maximum	8.83
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	6.92
Q1	7.33
median	7.58
Q3	7.75
95-th percentile	8
Maximum	8.83
Range	8.83
Interquartile range (IQR)	0.42

Descriptive statistics

Standard deviation	0.398442087
Coefficient of variation (CV)	0.05298132092
Kurtosis	94.7532297
Mean	7.520425691
Median Absolute Deviation (MAD)	0.17
Skewness	-5.195526489
Sum	10069.85
Variance	0.1587560967
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=35)

Value	Count	Frequency (%)
7.5	166	12.4%
7.58	166	12.4%
7.67	148	11.1%
7.75	126	9.4%
7.42	116	8.7%
7.33	111	8.3%
7.83	89	6.6%
7.25	64	4.8%
7.17	56	4.2%
7.92	45	3.4%
Other values (25)	252	18.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
6.08	1	0.1%
6.17	2	0.1%
6.33	3	0.2%
6.42	1	0.1%
6.5	9	0.7%
6.58	5	0.4%
6.67	5	0.4%
6.75	10	0.7%
6.83	17	1.3%

Value	Count	Frequency (%)
8.83	1	0.1%
8.67	4	0.3%
8.58	2	0.1%
8.5	5	0.4%
8.42	5	0.4%
8.33	5	0.4%
8.25	7	0.5%
8.17	18	1.3%
8.08	14	1.0%
8	41	3.1%

Aftertaste
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	35
Distinct (%)	2.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.401082898

Minimum	0
Maximum	8.67
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	6.83
Q1	7.25
median	7.42
Q3	7.58
95-th percentile	7.92
Maximum	8.67
Range	8.67
Interquartile range (IQR)	0.33

Descriptive statistics

Standard deviation	0.404463447
Coefficient of variation (CV)	0.05464922534
Kurtosis	83.55698524
Mean	7.401082898
Median Absolute Deviation (MAD)	0.17
Skewness	-4.79095828
Sum	9910.05
Variance	0.16359068
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=35)

Value	Count	Frequency (%)
7.5	164	12.2%
7.33	153	11.4%
7.42	129	9.6%
7.58	126	9.4%
7.25	104	7.8%
7.67	102	7.6%
7.17	91	6.8%
7.75	87	6.5%
7.83	65	4.9%
7	62	4.6%
Other values (25)	256	19.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
6.17	8	0.6%
6.25	1	0.1%
6.33	6	0.4%
6.42	4	0.3%
6.5	7	0.5%
6.58	6	0.4%
6.67	14	1.0%
6.75	10	0.7%
6.83	36	2.7%

Value	Count	Frequency (%)
8.67	1	0.1%
8.58	2	0.1%
8.5	4	0.3%
8.42	3	0.2%
8.33	2	0.1%
8.25	4	0.3%
8.17	7	0.5%
8.08	7	0.5%
8	27	2.0%
7.92	22	1.6%

Acidity
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	31
Distinct (%)	2.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.535705751

Minimum	0
Maximum	8.75
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	7
Q1	7.33
median	7.58
Q3	7.75
95-th percentile	8.08
Maximum	8.75
Range	8.75
Interquartile range (IQR)	0.42

Descriptive statistics

Standard deviation	0.3798266933
Coefficient of variation (CV)	0.05040359933
Kurtosis	116.1394574
Mean	7.535705751
Median Absolute Deviation (MAD)	0.17
Skewness	-5.943258891
Sum	10090.31
Variance	0.1442683169
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=31)

Value	Count	Frequency (%)
7.5	162	12.1%
7.58	154	11.5%
7.67	146	10.9%
7.42	129	9.6%
7.75	126	9.4%
7.33	111	8.3%
7.25	86	6.4%
7.83	78	5.8%
7.17	74	5.5%
8	50	3.7%
Other values (21)	223	16.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
5.25	1	0.1%
6.08	1	0.1%
6.25	1	0.1%
6.5	1	0.1%
6.67	5	0.4%
6.75	6	0.4%
6.83	12	0.9%
6.92	10	0.7%
7	32	2.4%

Value	Count	Frequency (%)
8.75	1	0.1%
8.58	1	0.1%
8.5	7	0.5%
8.42	6	0.4%
8.33	9	0.7%
8.25	6	0.4%
8.17	14	1.0%
8.08	25	1.9%
8	50	3.7%
7.92	47	3.5%

Body
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	33
Distinct (%)	2.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.517498133

Minimum	0
Maximum	8.58
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	7.08
Q1	7.33
median	7.5
Q3	7.67
95-th percentile	8
Maximum	8.58
Range	8.58
Interquartile range (IQR)	0.34

Descriptive statistics

Standard deviation	0.3700639451
Coefficient of variation (CV)	0.04922700857
Kurtosis	129.9339034
Mean	7.517498133
Median Absolute Deviation (MAD)	0.17
Skewness	-6.796184885
Sum	10065.93
Variance	0.1369473234
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=33)

Value	Count	Frequency (%)
7.5	201	15.0%
7.67	154	11.5%
7.58	138	10.3%
7.33	131	9.8%
7.42	127	9.5%
7.75	111	8.3%
7.25	87	6.5%
7.83	85	6.3%
7.17	68	5.1%
7.92	52	3.9%
Other values (23)	185	13.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
5.08	1	0.1%
5.17	1	0.1%
5.25	1	0.1%
6.33	2	0.1%
6.42	1	0.1%
6.5	1	0.1%
6.67	2	0.1%
6.75	4	0.3%
6.83	4	0.3%

Value	Count	Frequency (%)
8.58	1	0.1%
8.5	3	0.2%
8.42	3	0.2%
8.33	6	0.4%
8.25	7	0.5%
8.17	7	0.5%
8.08	21	1.6%
8	34	2.5%
7.92	52	3.9%
7.83	85	6.3%

Balance
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	33
Distinct (%)	2.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.518013443

Minimum	0
Maximum	8.75
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	6.92
Q1	7.33
median	7.5
Q3	7.75
95-th percentile	8.08
Maximum	8.75
Range	8.75
Interquartile range (IQR)	0.42

Descriptive statistics

Standard deviation	0.4089432915
Coefficient of variation (CV)	0.0543951264
Kurtosis	85.63351803
Mean	7.518013443
Median Absolute Deviation (MAD)	0.17
Skewness	-4.783035801
Sum	10066.62
Variance	0.1672346157
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=33)

Value	Count	Frequency (%)
7.5	176	13.1%
7.67	148	11.1%
7.58	131	9.8%
7.42	121	9.0%
7.75	107	8.0%
7.83	101	7.5%
7.33	99	7.4%
7.17	72	5.4%
7.25	64	4.8%
7	47	3.5%
Other values (23)	273	20.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
5.25	1	0.1%
6.08	1	0.1%
6.17	3	0.2%
6.33	1	0.1%
6.42	1	0.1%
6.5	2	0.1%
6.58	3	0.2%
6.67	4	0.3%
6.75	7	0.5%

Value	Count	Frequency (%)
8.75	2	0.1%
8.58	7	0.5%
8.5	7	0.5%
8.42	7	0.5%
8.33	7	0.5%
8.25	8	0.6%
8.17	17	1.3%
8.08	16	1.2%
8	46	3.4%
7.92	42	3.1%

Uniformity
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9.834876774

Minimum	0
Maximum	10
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	8.67
Q1	10
median	10
Q3	10
95-th percentile	10
Maximum	10
Range	10
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.5545906088
Coefficient of variation (CV)	0.05639019396
Kurtosis	85.35978352
Mean	9.834876774
Median Absolute Deviation (MAD)	0
Skewness	-6.966567106
Sum	13168.9
Variance	0.3075707434
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
10	1152	86.0%
9.33	116	8.7%
8.67	31	2.3%
8	25	1.9%
6.67	7	0.5%
6	3	0.2%
7.33	2	0.1%
9.5	1	0.1%
9	1	0.1%
0	1	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
6	3	0.2%
6.67	7	0.5%
7.33	2	0.1%
8	25	1.9%
8.67	31	2.3%
9	1	0.1%
9.33	116	8.7%
9.5	1	0.1%
10	1152	86.0%

Value	Count	Frequency (%)
10	1152	86.0%
9.5	1	0.1%
9.33	116	8.7%
9	1	0.1%
8.67	31	2.3%
8	25	1.9%
7.33	2	0.1%
6.67	7	0.5%
6	3	0.2%
0	1	0.1%

Clean.Cup
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	11
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9.83510829

Minimum	0
Maximum	10
Zeros	2
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	9.33
Q1	10
median	10
Q3	10
95-th percentile	10
Maximum	10
Range	10
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.7639459063
Coefficient of variation (CV)	0.07767539348
Kurtosis	70.51362253
Mean	9.83510829
Median Absolute Deviation (MAD)	0
Skewness	-7.44352063
Sum	13169.21
Variance	0.5836133478
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
10	1219	91.0%
9.33	61	4.6%
8.67	16	1.2%
6.67	13	1.0%
8	13	1.0%
6	6	0.4%
5.33	3	0.2%
7.33	3	0.2%
2.67	2	0.1%
0	2	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	2	0.1%
1.33	1	0.1%
2.67	2	0.1%
5.33	3	0.2%
6	6	0.4%
6.67	13	1.0%
7.33	3	0.2%
8	13	1.0%
8.67	16	1.2%
9.33	61	4.6%

Value	Count	Frequency (%)
10	1219	91.0%
9.33	61	4.6%
8.67	16	1.2%
8	13	1.0%
7.33	3	0.2%
6.67	13	1.0%
6	6	0.4%
5.33	3	0.2%
2.67	2	0.1%
1.33	1	0.1%

Sweetness
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	17
Distinct (%)	1.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9.856691561

Minimum	0
Maximum	10
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	9.33
Q1	10
median	10
Q3	10
95-th percentile	10
Maximum	10
Range	10
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.6161019777
Coefficient of variation (CV)	0.06250596094
Kurtosis	85.32969061
Mean	9.856691561
Median Absolute Deviation (MAD)	0
Skewness	-7.559007962
Sum	13198.11
Variance	0.3795816469
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=17)

Value	Count	Frequency (%)
10	1218	91.0%
9.33	61	4.6%
8.67	12	0.9%
8	11	0.8%
6.67	8	0.6%
7.75	7	0.5%
7.58	5	0.4%
6	3	0.2%
7.42	3	0.2%
7.92	2	0.1%
Other values (7)	9	0.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
1.33	1	0.1%
6	3	0.2%
6.67	8	0.6%
7.08	1	0.1%
7.42	3	0.2%
7.5	1	0.1%
7.58	5	0.4%
7.67	2	0.1%
7.75	7	0.5%

Value	Count	Frequency (%)
10	1218	91.0%
9.33	61	4.6%
8.67	12	0.9%
8.42	1	0.1%
8	11	0.8%
7.92	2	0.1%
7.83	2	0.1%
7.75	7	0.5%
7.67	2	0.1%
7.58	5	0.4%

Cupper.Points
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	42
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.503375653

Minimum	0
Maximum	10
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	6.83
Q1	7.25
median	7.5
Q3	7.75
95-th percentile	8.08
Maximum	10
Range	10
Interquartile range (IQR)	0.5

Descriptive statistics

Standard deviation	0.4734642722
Coefficient of variation (CV)	0.06310016906
Kurtosis	49.71213566
Mean	7.503375653
Median Absolute Deviation (MAD)	0.25
Skewness	-2.815594635
Sum	10047.02
Variance	0.2241684171
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=42)

Value	Count	Frequency (%)
7.5	154	11.5%
7.58	138	10.3%
7.33	115	8.6%
7.67	115	8.6%
7.42	104	7.8%
7.83	87	6.5%
7.75	87	6.5%
7.25	85	6.3%
7.17	64	4.8%
7.92	55	4.1%
Other values (32)	335	25.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
5.17	1	0.1%
5.25	1	0.1%
5.42	1	0.1%
6	1	0.1%
6.17	3	0.2%
6.25	1	0.1%
6.33	3	0.2%
6.42	5	0.4%
6.5	6	0.4%

Value	Count	Frequency (%)
10	4	0.3%
9.25	1	0.1%
9	1	0.1%
8.83	1	0.1%
8.75	1	0.1%
8.67	2	0.1%
8.58	6	0.4%
8.5	8	0.6%
8.42	6	0.4%
8.33	9	0.7%

Total.Cup.Points
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	180
Distinct (%)	13.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	82.08985063

Minimum	0
Maximum	90.58
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	77.83
Q1	81.08
median	82.5
Q3	83.67
95-th percentile	85.5
Maximum	90.58
Range	90.58
Interquartile range (IQR)	2.59

Descriptive statistics

Standard deviation	3.500575457
Coefficient of variation (CV)	0.04264321874
Kurtosis	228.0755525
Mean	82.08985063
Median Absolute Deviation (MAD)	1.25
Skewness	-10.44216733
Sum	109918.31
Variance	12.25402853
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
83	39	2.9%
83.17	38	2.8%
82.42	32	2.4%
82.75	30	2.2%
82.33	29	2.2%
82.67	26	1.9%
81.5	26	1.9%
81.83	26	1.9%
82.92	26	1.9%
83.25	25	1.9%
Other values (170)	1042	77.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
59.83	1	0.1%
63.08	1	0.1%
67.92	1	0.1%
68.33	1	0.1%
69.17	2	0.1%
69.33	1	0.1%
70.67	1	0.1%
70.75	1	0.1%
71	1	0.1%

Value	Count	Frequency (%)
90.58	1	0.1%
89.92	1	0.1%
89.75	1	0.1%
89	1	0.1%
88.83	2	0.1%
88.75	1	0.1%
88.67	1	0.1%
88.42	1	0.1%
88.25	1	0.1%
88.08	1	0.1%

Moisture
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	23
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.0883793876

Minimum	0
Maximum	0.28
Zeros	264
Zeros (%)	19.7%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0.09
median	0.11
Q3	0.12
95-th percentile	0.13
Maximum	0.28
Range	0.28
Interquartile range (IQR)	0.03

Descriptive statistics

Standard deviation	0.04828743714
Coefficient of variation (CV)	0.5463653737
Kurtosis	-0.1700121692
Mean	0.0883793876
Median Absolute Deviation (MAD)	0.01
Skewness	-0.9928607
Sum	118.34
Variance	0.002331676585
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=23)

Value	Count	Frequency (%)
0.11	383	28.6%
0.12	294	22.0%
0	264	19.7%
0.1	182	13.6%
0.13	76	5.7%
0.09	27	2.0%
0.14	23	1.7%
0.08	16	1.2%
0.01	15	1.1%
0.15	8	0.6%
Other values (13)	51	3.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	264	19.7%
0.01	15	1.1%
0.02	7	0.5%
0.03	4	0.3%
0.04	4	0.3%
0.05	8	0.6%
0.06	7	0.5%
0.07	5	0.4%
0.08	16	1.2%
0.09	27	2.0%

Value	Count	Frequency (%)
0.28	1	0.1%
0.22	1	0.1%
0.21	1	0.1%
0.2	3	0.2%
0.18	2	0.1%
0.17	3	0.2%
0.16	5	0.4%
0.15	8	0.6%
0.14	23	1.7%
0.13	76	5.7%

Category.One.Defects
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	18
Distinct (%)	1.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.4794622853

Minimum	0
Maximum	63
Zeros	1137
Zeros (%)	84.9%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	2
Maximum	63
Range	63
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	2.549683472
Coefficient of variation (CV)	5.317797772
Kurtosis	308.7155768
Mean	0.4794622853
Median Absolute Deviation (MAD)	0
Skewness	15.06148967
Sum	642
Variance	6.500885809
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=18)

Value	Count	Frequency (%)
0	1137	84.9%
1	101	7.5%
2	38	2.8%
3	18	1.3%
4	16	1.2%
5	9	0.7%
10	4	0.3%
6	3	0.2%
7	3	0.2%
31	2	0.1%
Other values (8)	8	0.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1137	84.9%
1	101	7.5%
2	38	2.8%
3	18	1.3%
4	16	1.2%
5	9	0.7%
6	3	0.2%
7	3	0.2%
8	1	0.1%
9	1	0.1%

Value	Count	Frequency (%)
63	1	0.1%
31	2	0.1%
23	1	0.1%
20	1	0.1%
15	1	0.1%
12	1	0.1%
11	1	0.1%
10	4	0.3%
9	1	0.1%
8	1	0.1%

Quakers
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	11
Distinct (%)	0.8%
Missing	1
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%
Mean	0.1733931241

Minimum	0
Maximum	11
Zeros	1244
Zeros (%)	92.9%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	11
Range	11
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.8321210408
Coefficient of variation (CV)	4.799042899
Kurtosis	58.33424418
Mean	0.1733931241
Median Absolute Deviation (MAD)	0
Skewness	6.936339775
Sum	232
Variance	0.6924254265
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
0	1244	92.9%
1	39	2.9%
2	30	2.2%
4	5	0.4%
5	5	0.4%
3	5	0.4%
6	4	0.3%
7	3	0.2%
11	1	0.1%
9	1	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1244	92.9%
1	39	2.9%
2	30	2.2%
3	5	0.4%
4	5	0.4%
5	5	0.4%
6	4	0.3%
7	3	0.2%
8	1	0.1%
9	1	0.1%

Value	Count	Frequency (%)
11	1	0.1%
9	1	0.1%
8	1	0.1%
7	3	0.2%
6	4	0.3%
5	5	0.4%
4	5	0.4%
3	5	0.4%
2	30	2.2%
1	39	2.9%

Color
Categorical

HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	0.4%
Missing	218
Missing (%)	16.3%
Memory size	86.3 KiB

Green	870
Bluish-Green	114
Blue-Green	85
None	52

Length

Max length	12
Median length	5
Mean length	6.044603033
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Green
2nd row	Green
3rd row	Green
4th row	Green
5th row	Bluish-Green

Common Values

Value	Count	Frequency (%)
Green	870	65.0%
Bluish-Green	114	8.5%
Blue-Green	85	6.3%
None	52	3.9%
(Missing)	218	16.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
green	870	77.6%
bluish-green	114	10.2%
blue-green	85	7.6%
none	52	4.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Category.Two.Defects
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	38
Distinct (%)	2.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.556385362

Minimum	0
Maximum	55
Zeros	373
Zeros (%)	27.9%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	2
Q3	4
95-th percentile	13
Maximum	55
Range	55
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	5.312540717
Coefficient of variation (CV)	1.493803448
Kurtosis	20.08268531
Mean	3.556385362
Median Absolute Deviation (MAD)	2
Skewness	3.667136229
Sum	4762
Variance	28.22308887
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=38)

Value	Count	Frequency (%)
0	373	27.9%
1	207	15.5%
2	182	13.6%
3	134	10.0%
4	118	8.8%
5	73	5.5%
6	44	3.3%
7	41	3.1%
8	29	2.2%
9	23	1.7%
Other values (28)	115	8.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	373	27.9%
1	207	15.5%
2	182	13.6%
3	134	10.0%
4	118	8.8%
5	73	5.5%
6	44	3.3%
7	41	3.1%
8	29	2.2%
9	23	1.7%

Value	Count	Frequency (%)
55	1	0.1%
47	1	0.1%
45	1	0.1%
40	1	0.1%
38	1	0.1%
34	1	0.1%
32	1	0.1%
31	1	0.1%
30	2	0.1%
29	2	0.1%

Expiration
Categorical

HIGH CARDINALITY

Distinct	566
Distinct (%)	42.3%
Missing	0
Missing (%)	0.0%
Memory size	106.7 KiB

July 11th, 2013	25
December 26th, 2014	25
June 6th, 2013	19
August 30th, 2013	18
July 26th, 2013	15
Other values (561)	1237

Length

Max length	20
Median length	16
Mean length	16.59297984
Min length	13

Characters and Unicode

Total characters	1
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	282 ?
Unique (%)	21.1%

Sample

1st row	April 3rd, 2016
2nd row	April 3rd, 2016
3rd row	May 31st, 2011
4th row	March 25th, 2016
5th row	April 3rd, 2016

Common Values

Value	Count	Frequency (%)
July 11th, 2013	25	1.9%
December 26th, 2014	25	1.9%
June 6th, 2013	19	1.4%
August 30th, 2013	18	1.3%
July 26th, 2013	15	1.1%
October 7th, 2016	13	1.0%
March 29th, 2014	13	1.0%
September 27th, 2013	13	1.0%
June 17th, 2011	12	0.9%
October 20th, 2018	11	0.8%
Other values (556)	1175	87.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2013	316	7.9%
2015	262	6.5%
2016	197	4.9%
june	162	4.0%
2014	155	3.9%
2018	143	3.6%
july	130	3.2%
april	129	3.2%
may	128	3.2%
2017	127	3.2%
Other values (42)	2268	56.5%

Most occurring characters

Value	Count	Frequency (%)
	1	100.0%

Most occurring categories

Value	Count	Frequency (%)
Control	1	100.0%

Most frequent character per category

Control

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
	1	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	1	100.0%

Certification.Body
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	26
Distinct (%)	1.9%
Missing	0
Missing (%)	0.0%
Memory size	125.0 KiB

Specialty Coffee Association	313
AMECAFE	205
Almacafé	178
Asociacion Nacional Del Café	155
Brazil Specialty Coffee Association	67
Other values (21)	421

Length

Max length	85
Median length	28
Mean length	23.10455564
Min length	7

Characters and Unicode

Total characters	1
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	0.1%

Sample

1st row	METAD Agricultural Development plc
2nd row	METAD Agricultural Development plc
3rd row	Specialty Coffee Association
4th row	METAD Agricultural Development plc
5th row	METAD Agricultural Development plc

Common Values

Value	Count	Frequency (%)
Specialty Coffee Association	313	23.4%
AMECAFE	205	15.3%
Almacafé	178	13.3%
Asociacion Nacional Del Café	155	11.6%
Brazil Specialty Coffee Association	67	5.0%
Instituto Hondureño del Café	60	4.5%
Blossom Valley International	58	4.3%
Africa Fine Coffee Association	49	3.7%
Specialty Coffee Association of Costa Rica	43	3.2%
NUCOFFEE	36	2.7%
Other values (16)	175	13.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
coffee	590	15.3%
association	504	13.1%
specialty	449	11.7%
café	225	5.8%
del	224	5.8%
amecafe	205	5.3%
almacafé	178	4.6%
asociacion	155	4.0%
nacional	155	4.0%
of	69	1.8%
Other values (51)	1096	28.5%

Most occurring characters

Value	Count	Frequency (%)
	1	100.0%

Most occurring categories

Value	Count	Frequency (%)
Control	1	100.0%

Most frequent character per category

Control

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
	1	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	1	100.0%

Certification.Address
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	32
Distinct (%)	2.4%
Missing	0
Missing (%)	0.0%
Memory size	137.3 KiB

36d0d00a3724338ba7937c52a378d085f2172daa	293
59e396ad6e22a1c22b248f958e1da2bd8af85272	204
e493c36c2d076bf273064f7ac23ad562af257a25	178
b1f20fe3a819fd6b2ee0eb8fdc3da256604f1e53	155
3297cfa4c538e3dd03f72cc4082c54f7999e1f9d	67
Other values (27)	442

Length

Max length	40
Median length	40
Mean length	40
Min length	40

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	0.4%

Sample

1st row	309fcf77415a3661ae83e027f7e5f05dad786e44
2nd row	309fcf77415a3661ae83e027f7e5f05dad786e44
3rd row	36d0d00a3724338ba7937c52a378d085f2172daa
4th row	309fcf77415a3661ae83e027f7e5f05dad786e44
5th row	309fcf77415a3661ae83e027f7e5f05dad786e44

Common Values

Value	Count	Frequency (%)
36d0d00a3724338ba7937c52a378d085f2172daa	293	21.9%
59e396ad6e22a1c22b248f958e1da2bd8af85272	204	15.2%
e493c36c2d076bf273064f7ac23ad562af257a25	178	13.3%
b1f20fe3a819fd6b2ee0eb8fdc3da256604f1e53	155	11.6%
3297cfa4c538e3dd03f72cc4082c54f7999e1f9d	67	5.0%
b4660a57e9f8cc613ae5b8f02bfce8634c763ab4	60	4.5%
fc45352eee499d8470cf94c9827922fb745bf815	58	4.3%
073285c0d45e2f5539012d969937e529564fa6fe	48	3.6%
8e0b118f3cf3121ab27c5387deacdb7d4d2a60b1	42	3.1%
567f200bcc17a90070cb952647bf88141ad9c80c	36	2.7%
Other values (22)	198	14.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
36d0d00a3724338ba7937c52a378d085f2172daa	293	21.9%
59e396ad6e22a1c22b248f958e1da2bd8af85272	204	15.2%
e493c36c2d076bf273064f7ac23ad562af257a25	178	13.3%
b1f20fe3a819fd6b2ee0eb8fdc3da256604f1e53	155	11.6%
3297cfa4c538e3dd03f72cc4082c54f7999e1f9d	67	5.0%
b4660a57e9f8cc613ae5b8f02bfce8634c763ab4	60	4.5%
fc45352eee499d8470cf94c9827922fb745bf815	58	4.3%
073285c0d45e2f5539012d969937e529564fa6fe	48	3.6%
8e0b118f3cf3121ab27c5387deacdb7d4d2a60b1	42	3.1%
567f200bcc17a90070cb952647bf88141ad9c80c	36	2.7%
Other values (22)	198	14.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Certification.Contact
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	29
Distinct (%)	2.2%
Missing	0
Missing (%)	0.0%
Memory size	137.3 KiB

0878a7d4b9d35ddbf0fe2ce69a2062cceb45a660	295
0eb4ee5b3f47b20b049548a2fd1e7d4a2b70d0a7	204
70d3c0c26f89e00fdae6fb39ff54f0d2eb1c38ab	178
724f04ad10ed31dbb9d260f0dfd221ba48be8a95	155
8900f0bf1d0b2bafe6807a73562c7677d57eb980	67
Other values (24)	440

Length

Max length	40
Median length	40
Mean length	40
Min length	40

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	0.2%

Sample

1st row	19fef5a731de2db57d16da10287413f5f99bc2dd
2nd row	19fef5a731de2db57d16da10287413f5f99bc2dd
3rd row	0878a7d4b9d35ddbf0fe2ce69a2062cceb45a660
4th row	19fef5a731de2db57d16da10287413f5f99bc2dd
5th row	19fef5a731de2db57d16da10287413f5f99bc2dd

Common Values

Value	Count	Frequency (%)
0878a7d4b9d35ddbf0fe2ce69a2062cceb45a660	295	22.0%
0eb4ee5b3f47b20b049548a2fd1e7d4a2b70d0a7	204	15.2%
70d3c0c26f89e00fdae6fb39ff54f0d2eb1c38ab	178	13.3%
724f04ad10ed31dbb9d260f0dfd221ba48be8a95	155	11.6%
8900f0bf1d0b2bafe6807a73562c7677d57eb980	67	5.0%
7f521ca403540f81ec99daec7da19c2788393880	60	4.5%
de73fc9412358b523d3a641501e542f31d2668b0	58	4.3%
c4ab13415cdd69376a93780c0166e7b1a10481ea	49	3.7%
5eb2b7129d9714c43825e44dc3bca9423de209e9	43	3.2%
aa2ff513ffb9c844462a1fb07c599bce7f3bb53d	36	2.7%
Other values (19)	194	14.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
0878a7d4b9d35ddbf0fe2ce69a2062cceb45a660	295	22.0%
0eb4ee5b3f47b20b049548a2fd1e7d4a2b70d0a7	204	15.2%
70d3c0c26f89e00fdae6fb39ff54f0d2eb1c38ab	178	13.3%
724f04ad10ed31dbb9d260f0dfd221ba48be8a95	155	11.6%
8900f0bf1d0b2bafe6807a73562c7677d57eb980	67	5.0%
7f521ca403540f81ec99daec7da19c2788393880	60	4.5%
de73fc9412358b523d3a641501e542f31d2668b0	58	4.3%
c4ab13415cdd69376a93780c0166e7b1a10481ea	49	3.7%
5eb2b7129d9714c43825e44dc3bca9423de209e9	43	3.2%
aa2ff513ffb9c844462a1fb07c599bce7f3bb53d	36	2.7%
Other values (19)	194	14.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

unit_of_measurement
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	86.5 KiB

m	1157
ft	182

Length

Max length	2
Median length	1
Mean length	1.13592233
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	m
2nd row	m
3rd row	m
4th row	m
5th row	m

Common Values

Value	Count	Frequency (%)
m	1157	86.4%
ft	182	13.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
m	1157	86.4%
ft	182	13.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

altitude_low_meters
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	198
Distinct (%)	17.9%
Missing	230
Missing (%)	17.2%
Infinite	0
Infinite (%)	0.0%
Mean	1750.713315

Minimum	1
Maximum	190164
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	1
5-th percentile	442
Q1	1100
median	1310.64
Q3	1600
95-th percentile	1850
Maximum	190164
Range	190163
Interquartile range (IQR)	500

Descriptive statistics

Standard deviation	8669.440545
Coefficient of variation (CV)	4.951947569
Kurtosis	423.9278958
Mean	1750.713315
Median Absolute Deviation (MAD)	239.36
Skewness	20.3231837
Sum	1941541.066
Variance	75159199.36
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1200	82	6.1%
1600	66	4.9%
1400	59	4.4%
1100	55	4.1%
1500	54	4.0%
1300	48	3.6%
1800	41	3.1%
1250	38	2.8%
1700	36	2.7%
1000	34	2.5%
Other values (188)	596	44.5%
(Missing)	230	17.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	14	1.0%
12	3	0.2%
13	2	0.1%
40	1	0.1%
50	1	0.1%
100	2	0.1%
110	1	0.1%
125	1	0.1%
150	2	0.1%
157.8864	3	0.2%

Value	Count	Frequency (%)
190164	2	0.1%
110000	1	0.1%
11000	1	0.1%
4287	1	0.1%
4001	1	0.1%
3845	1	0.1%
3825	1	0.1%
3800	1	0.1%
3500	1	0.1%
3280	3	0.2%

altitude_high_meters
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	198
Distinct (%)	17.9%
Missing	230
Missing (%)	17.2%
Infinite	0
Infinite (%)	0.0%
Mean	1799.347775

Minimum	1
Maximum	190164
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	1
5-th percentile	442
Q1	1100
median	1350
Q3	1650
95-th percentile	1950
Maximum	190164
Range	190163
Interquartile range (IQR)	550

Descriptive statistics

Standard deviation	8668.805771
Coefficient of variation (CV)	4.817748904
Kurtosis	423.595361
Mean	1799.347775
Median Absolute Deviation (MAD)	250
Skewness	20.31093398
Sum	1995476.682
Variance	75148193.5
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1200	66	4.9%
1400	63	4.7%
1100	54	4.0%
1500	51	3.8%
1300	46	3.4%
1800	44	3.3%
1700	42	3.1%
1250	39	2.9%
1600	35	2.6%
1000	35	2.6%
Other values (188)	634	47.3%
(Missing)	230	17.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	12	0.9%
12	3	0.2%
13	2	0.1%
40	1	0.1%
50	1	0.1%
100	1	0.1%
110	1	0.1%
125	1	0.1%
150	2	0.1%
157.8864	3	0.2%

Value	Count	Frequency (%)
190164	2	0.1%
110000	1	0.1%
11000	1	0.1%
5900	1	0.1%
4287	1	0.1%
4001	1	0.1%
3845	1	0.1%
3825	1	0.1%
3800	1	0.1%
3500	1	0.1%

altitude_mean_meters
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	211
Distinct (%)	19.0%
Missing	230
Missing (%)	17.2%
Infinite	0
Infinite (%)	0.0%
Mean	1775.030545

Minimum	1
Maximum	190164
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	20.9 KiB

Quantile statistics

Minimum	1
5-th percentile	442
Q1	1100
median	1310.64
Q3	1600
95-th percentile	1892
Maximum	190164
Range	190163
Interquartile range (IQR)	500

Descriptive statistics

Standard deviation	8668.62608
Coefficient of variation (CV)	4.883648963
Kurtosis	423.8594836
Mean	1775.030545
Median Absolute Deviation (MAD)	251.64
Skewness	20.32052739
Sum	1968508.874
Variance	75145078.11
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1200	67	5.0%
1100	53	4.0%
1400	52	3.9%
1300	50	3.7%
1500	44	3.3%
1250	40	3.0%
1000	36	2.7%
1600	36	2.7%
1700	36	2.7%
1750	34	2.5%
Other values (201)	661	49.4%
(Missing)	230	17.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	12	0.9%
12	3	0.2%
13	2	0.1%
40	1	0.1%
50	1	0.1%
100	1	0.1%
110	1	0.1%
125	1	0.1%
150	2	0.1%
157.8864	3	0.2%

Value	Count	Frequency (%)
190164	2	0.1%
110000	1	0.1%
11000	1	0.1%
4287	1	0.1%
4001	1	0.1%
3850	1	0.1%
3845	1	0.1%
3825	1	0.1%
3800	1	0.1%
3500	1	0.1%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	Species	Owner	Country.of.Origin	Farm.Name	Lot.Number	Mill	ICO.Number	Company	Altitude	Region	Producer	Number.of.Bags	Bag.Weight	In.Country.Partner	Harvest.Year	Grading.Date	Owner.1	Variety	Processing.Method	Aroma	Flavor	Aftertaste	Acidity	Body	Balance	Uniformity	Clean.Cup	Sweetness	Cupper.Points	Total.Cup.Points	Moisture	Color	Category.Two.Defects	Expiration	Certification.Body	Certification.Address	Certification.Contact	unit_of_measurement	altitude_low_meters	altitude_high_meters	altitude_mean_meters
0	Arabica	metad plc	Ethiopia	metad plc	NaN	metad plc	2014/2015	metad agricultural developmet plc	1950-2200	guji-hambela	METAD PLC	300	60 kg	METAD Agricultural Development plc	2014	April 4th, 2015	metad plc	NaN	Washed / Wet	8.67	8.83	8.67	8.75	8.50	8.42	10.00	10.0	10.00	8.75	90.58	0.12	Green	0	April 3rd, 2016	METAD Agricultural Development plc	309fcf77415a3661ae83e027f7e5f05dad786e44	19fef5a731de2db57d16da10287413f5f99bc2dd	m	1950.0	2200.0	2075.0
1	Arabica	metad plc	Ethiopia	metad plc	NaN	metad plc	2014/2015	metad agricultural developmet plc	1950-2200	guji-hambela	METAD PLC	300	60 kg	METAD Agricultural Development plc	2014	April 4th, 2015	metad plc	Other	Washed / Wet	8.75	8.67	8.50	8.58	8.42	8.42	10.00	10.0	10.00	8.58	89.92	0.12	Green	1	April 3rd, 2016	METAD Agricultural Development plc	309fcf77415a3661ae83e027f7e5f05dad786e44	19fef5a731de2db57d16da10287413f5f99bc2dd	m	1950.0	2200.0	2075.0
2	Arabica	grounds for health admin	Guatemala	san marcos barrancas "san cristobal cuch	NaN	NaN	NaN	NaN	1600 - 1800 m	NaN	NaN	5	1	Specialty Coffee Association	NaN	May 31st, 2010	Grounds for Health Admin	Bourbon	NaN	8.42	8.50	8.42	8.42	8.33	8.42	10.00	10.0	10.00	9.25	89.75	0.00	NaN	0	May 31st, 2011	Specialty Coffee Association	36d0d00a3724338ba7937c52a378d085f2172daa	0878a7d4b9d35ddbf0fe2ce69a2062cceb45a660	m	1600.0	1800.0	1700.0
3	Arabica	yidnekachew dabessa	Ethiopia	yidnekachew dabessa coffee plantation	NaN	wolensu	NaN	yidnekachew debessa coffee plantation	1800-2200	oromia	Yidnekachew Dabessa Coffee Plantation	320	60 kg	METAD Agricultural Development plc	2014	March 26th, 2015	Yidnekachew Dabessa	NaN	Natural / Dry	8.17	8.58	8.42	8.42	8.50	8.25	10.00	10.0	10.00	8.67	89.00	0.11	Green	2	March 25th, 2016	METAD Agricultural Development plc	309fcf77415a3661ae83e027f7e5f05dad786e44	19fef5a731de2db57d16da10287413f5f99bc2dd	m	1800.0	2200.0	2000.0
4	Arabica	metad plc	Ethiopia	metad plc	NaN	metad plc	2014/2015	metad agricultural developmet plc	1950-2200	guji-hambela	METAD PLC	300	60 kg	METAD Agricultural Development plc	2014	April 4th, 2015	metad plc	Other	Washed / Wet	8.25	8.50	8.25	8.50	8.42	8.33	10.00	10.0	10.00	8.58	88.83	0.12	Green	2	April 3rd, 2016	METAD Agricultural Development plc	309fcf77415a3661ae83e027f7e5f05dad786e44	19fef5a731de2db57d16da10287413f5f99bc2dd	m	1950.0	2200.0	2075.0
5	Arabica	ji-ae ahn	Brazil	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	100	30 kg	Specialty Coffee Institute of Asia	2013	September 3rd, 2013	Ji-Ae Ahn	NaN	Natural / Dry	8.58	8.42	8.42	8.50	8.25	8.33	10.00	10.0	10.00	8.33	88.83	0.11	Bluish-Green	1	September 3rd, 2014	Specialty Coffee Institute of Asia	726e4891cf2c9a4848768bd34b668124d12c4224	b70da261fcc84831e3e9620c30a8701540abc200	m	NaN	NaN	NaN
6	Arabica	hugo valdivia	Peru	NaN	NaN	hvc	NaN	richmond investment-coffee department	NaN	NaN	HVC	100	69 kg	Specialty Coffee Institute of Asia	2012	September 17th, 2012	Hugo Valdivia	Other	Washed / Wet	8.42	8.50	8.33	8.50	8.25	8.25	10.00	10.0	10.00	8.50	88.75	0.11	Bluish-Green	0	September 17th, 2013	Specialty Coffee Institute of Asia	726e4891cf2c9a4848768bd34b668124d12c4224	b70da261fcc84831e3e9620c30a8701540abc200	m	NaN	NaN	NaN
7	Arabica	ethiopia commodity exchange	Ethiopia	aolme	NaN	c.p.w.e	010/0338	NaN	1570-1700	oromia	Bazen Agricultural & Industrial Dev't Plc	300	60 kg	Ethiopia Commodity Exchange	March 2010	September 2nd, 2010	Ethiopia Commodity Exchange	NaN	NaN	8.25	8.33	8.50	8.42	8.33	8.50	10.00	10.0	9.33	9.00	88.67	0.03	NaN	0	September 2nd, 2011	Ethiopia Commodity Exchange	a176532400aebdc345cf3d870f84ed3ecab6249e	61bbaf6a9f341e5782b8e7bd3ebf76aac89fe24b	m	1570.0	1700.0	1635.0
8	Arabica	ethiopia commodity exchange	Ethiopia	aolme	NaN	c.p.w.e	010/0338	NaN	1570-1700	oromiya	Bazen Agricultural & Industrial Dev't Plc	300	60 kg	Ethiopia Commodity Exchange	March 2010	September 2nd, 2010	Ethiopia Commodity Exchange	NaN	NaN	8.67	8.67	8.58	8.42	8.33	8.42	9.33	10.0	9.33	8.67	88.42	0.03	NaN	0	September 2nd, 2011	Ethiopia Commodity Exchange	a176532400aebdc345cf3d870f84ed3ecab6249e	61bbaf6a9f341e5782b8e7bd3ebf76aac89fe24b	m	1570.0	1700.0	1635.0
9	Arabica	diamond enterprise plc	Ethiopia	tulla coffee farm	NaN	tulla coffee farm	2014/15	diamond enterprise plc	1795-1850	snnp/kaffa zone,gimbowereda	Diamond Enterprise Plc	50	60 kg	METAD Agricultural Development plc	2014	March 30th, 2015	Diamond Enterprise Plc	Other	Natural / Dry	8.08	8.58	8.50	8.50	7.67	8.42	10.00	10.0	10.00	8.50	88.25	0.10	Green	4	March 29th, 2016	METAD Agricultural Development plc	309fcf77415a3661ae83e027f7e5f05dad786e44	19fef5a731de2db57d16da10287413f5f99bc2dd	m	1795.0	1850.0	1822.5

Last rows

	Species	Owner	Country.of.Origin	Farm.Name	Lot.Number	Mill	ICO.Number	Company	Altitude	Region	Producer	Number.of.Bags	Bag.Weight	In.Country.Partner	Harvest.Year	Grading.Date	Owner.1	Variety	Processing.Method	Aroma	Flavor	Aftertaste	Acidity	Body	Balance	Uniformity	Clean.Cup	Sweetness	Cupper.Points	Total.Cup.Points	Moisture	Category.One.Defects	Color	Category.Two.Defects	Expiration	Certification.Body	Certification.Address	Certification.Contact	unit_of_measurement	altitude_low_meters	altitude_high_meters	altitude_mean_meters
1329	Robusta	nitubaasa ltd	Uganda	kigezi coffee farmers association	NaN	nitubaasa	0	nitubaasa ltd	1745	western	Kigezi Coffee Farmers Association	20	60 kg	Uganda Coffee Development Authority	2013	June 27th, 2014	Nitubaasa Ltd	NaN	NaN	7.83	7.58	7.33	7.67	7.50	7.50	10.00	10.00	7.75	7.42	80.58	0.12	0	Green	2	June 27th, 2015	Uganda Coffee Development Authority	e36d0270932c3b657e96b7b0278dfd85dc0fe743	03077a1c6bac60e6f514691634a7f6eb5c85aae8	m	1745.0	1745.0	1745.0
1330	Robusta	mannya coffee project	Uganda	mannya coffee project	NaN	mannya coffee project	0	mannya coffee project	1200	southern	Mannya coffee project	6	60 kg	Uganda Coffee Development Authority	2013	June 27th, 2014	Mannya coffee project	NaN	NaN	7.75	7.42	7.33	7.58	7.67	7.58	10.00	10.00	7.67	7.50	80.50	0.12	0	Green	1	June 27th, 2015	Uganda Coffee Development Authority	e36d0270932c3b657e96b7b0278dfd85dc0fe743	03077a1c6bac60e6f514691634a7f6eb5c85aae8	m	1200.0	1200.0	1200.0
1331	Robusta	andrew hetzel	India	sethuraman estates	NaN	NaN	NaN	cafemakers	750m	chikmagalur	Nishant Gurjer	100	2 kg	Specialty Coffee Association	2014	May 19th, 2014	Andrew Hetzel	NaN	NaN	7.67	7.67	7.50	7.33	7.58	7.50	10.00	10.00	7.42	7.50	80.17	0.00	0	Bluish-Green	1	May 19th, 2015	Specialty Coffee Association	ff7c18ad303d4b603ac3f8cff7e611ffc735e720	352d0cf7f3e9be14dad7df644ad65efc27605ae2	m	750.0	750.0	750.0
1332	Robusta	andrew hetzel	India	sethuraman estates	NaN	sethuraman estates	NaN	cafemakers, llc	750m	chikmagalur	Nishant Gurjer	250	2 kg	Specialty Coffee Association	2013	June 20th, 2013	Andrew Hetzel	NaN	Natural / Dry	7.58	7.42	7.42	7.83	7.42	7.50	10.00	10.00	7.42	7.58	80.17	0.00	0	Green	0	June 20th, 2014	Specialty Coffee Association	ff7c18ad303d4b603ac3f8cff7e611ffc735e720	352d0cf7f3e9be14dad7df644ad65efc27605ae2	m	750.0	750.0	750.0
1333	Robusta	andrew hetzel	United States	sethuraman estates	NaN	sethuraman estates	NaN	cafemakers, llc	3000'	chikmagalur	Sethuraman Estates	100	1 kg	Specialty Coffee Association	2012	February 29th, 2012	Andrew Hetzel	Arusha	Natural / Dry	7.92	7.50	7.42	7.42	7.42	7.42	9.33	10.00	7.58	7.33	79.33	0.00	0	Green	0	February 28th, 2013	Specialty Coffee Association	ff7c18ad303d4b603ac3f8cff7e611ffc735e720	352d0cf7f3e9be14dad7df644ad65efc27605ae2	m	3000.0	3000.0	3000.0
1334	Robusta	luis robles	Ecuador	robustasa	Lavado 1	our own lab	NaN	robustasa	NaN	san juan, playas	Café Robusta del Ecuador S.A.	1	2 kg	Specialty Coffee Association	2016	January 19th, 2016	Luis Robles	NaN	NaN	7.75	7.58	7.33	7.58	5.08	7.83	10.00	10.00	7.75	7.83	78.75	0.00	0	Blue-Green	1	January 18th, 2017	Specialty Coffee Association	ff7c18ad303d4b603ac3f8cff7e611ffc735e720	352d0cf7f3e9be14dad7df644ad65efc27605ae2	m	NaN	NaN	NaN
1335	Robusta	luis robles	Ecuador	robustasa	Lavado 3	own laboratory	NaN	robustasa	40	san juan, playas	Café Robusta del Ecuador S.A.	1	2 kg	Specialty Coffee Association	2016	January 19th, 2016	Luis Robles	NaN	NaN	7.50	7.67	7.75	7.75	5.17	5.25	10.00	10.00	8.42	8.58	78.08	0.00	0	Blue-Green	0	January 18th, 2017	Specialty Coffee Association	ff7c18ad303d4b603ac3f8cff7e611ffc735e720	352d0cf7f3e9be14dad7df644ad65efc27605ae2	m	40.0	40.0	40.0
1336	Robusta	james moore	United States	fazenda cazengo	NaN	cafe cazengo	NaN	global opportunity fund	795 meters	kwanza norte province, angola	Cafe Cazengo	1	1 kg	Specialty Coffee Association	2014	December 23rd, 2014	James Moore	NaN	Natural / Dry	7.33	7.33	7.17	7.42	7.50	7.17	9.33	9.33	7.42	7.17	77.17	0.00	0	NaN	6	December 23rd, 2015	Specialty Coffee Association	ff7c18ad303d4b603ac3f8cff7e611ffc735e720	352d0cf7f3e9be14dad7df644ad65efc27605ae2	m	795.0	795.0	795.0
1337	Robusta	cafe politico	India	NaN	NaN	NaN	14-1118-2014-0087	cafe politico	NaN	NaN	NaN	1	5 lbs	Specialty Coffee Association	2013	August 25th, 2014	Cafe Politico	NaN	Natural / Dry	7.42	6.83	6.75	7.17	7.25	7.00	9.33	9.33	7.08	6.92	75.08	0.10	20	Green	1	August 25th, 2015	Specialty Coffee Association	ff7c18ad303d4b603ac3f8cff7e611ffc735e720	352d0cf7f3e9be14dad7df644ad65efc27605ae2	m	NaN	NaN	NaN
1338	Robusta	cafe politico	Vietnam	NaN	NaN	NaN	NaN	cafe politico	NaN	NaN	NaN	1	5 lbs	Specialty Coffee Association	2013	August 25th, 2014	Cafe Politico	NaN	Natural / Dry	6.75	6.67	6.50	6.83	6.92	6.83	9.33	9.33	6.67	7.92	73.75	0.12	63	None	9	August 25th, 2015	Specialty Coffee Association	ff7c18ad303d4b603ac3f8cff7e611ffc735e720	352d0cf7f3e9be14dad7df644ad65efc27605ae2	m	NaN	NaN	NaN

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

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Most occurring characters

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Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

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Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

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Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category